Detection of Clinically Relevant Copy Number Variants with Whole-Exome Sequencing

Authors

  • Joep de Ligt,

    1. Department of Human Genetics, Nijmegen Centre for Molecular Life Sciences, Institute for Genetic and Metabolic Disease, Radboud University Medical Centre, Nijmegen, The Netherlands
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    • These authors contributed equally to this work.

  • Philip M. Boone,

    1. Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas
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    • These authors contributed equally to this work.

  • Rolph Pfundt,

    1. Department of Human Genetics, Nijmegen Centre for Molecular Life Sciences, Institute for Genetic and Metabolic Disease, Radboud University Medical Centre, Nijmegen, The Netherlands
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  • Lisenka E.L.M. Vissers,

    1. Department of Human Genetics, Nijmegen Centre for Molecular Life Sciences, Institute for Genetic and Metabolic Disease, Radboud University Medical Centre, Nijmegen, The Netherlands
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  • Todd Richmond,

    1. Roche NimbleGen, Madison, Wisconsin
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  • Joel Geoghegan,

    1. Roche NimbleGen, Madison, Wisconsin
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  • Kathleen O'Moore,

    1. Roche NimbleGen, Madison, Wisconsin
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  • Nicole de Leeuw,

    1. Department of Human Genetics, Nijmegen Centre for Molecular Life Sciences, Institute for Genetic and Metabolic Disease, Radboud University Medical Centre, Nijmegen, The Netherlands
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  • Christine Shaw,

    1. Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas
    2. Roche NimbleGen, Madison, Wisconsin
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  • Han G. Brunner,

    1. Department of Human Genetics, Nijmegen Centre for Molecular Life Sciences, Institute for Genetic and Metabolic Disease, Radboud University Medical Centre, Nijmegen, The Netherlands
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  • James R. Lupski,

    1. Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas
    2. Department of Pediatrics, Baylor College of Medicine, Houston, Texas
    3. Texas Children's Hospital, Houston, Texas
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  • Joris A. Veltman,

    1. Department of Human Genetics, Nijmegen Centre for Molecular Life Sciences, Institute for Genetic and Metabolic Disease, Radboud University Medical Centre, Nijmegen, The Netherlands
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  • Jayne Y. Hehir-Kwa

    Corresponding author
    • Department of Human Genetics, Nijmegen Centre for Molecular Life Sciences, Institute for Genetic and Metabolic Disease, Radboud University Medical Centre, Nijmegen, The Netherlands
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  • Contract grant sponsors: European Union TECHGENE Project (Health-F5-2009-223143); GEUVADIS Project (Health-F7-2010-261123); European Research Council (DENOVO 281964).

  • Communicated by Johan T. den Dunnen

Correspondence to: Jayne Hehir-Kwa, Department of Human Genetics, Nijmegen Centre for Molecular Life Sciences, Institute for Genetic and Metabolic Disease, Radboud University Medical Centre, Nijmegen, PO Box 9101, 6500 HB. E-mail: J.Hehir@gen.umcn.nl

ABSTRACT

Copy number variation (CNV) is a common source of genetic variation that has been implicated in many genomic disorders. This has resulted in the widespread application of genomic microarrays as a first-tier diagnostic tool for CNV detection. More recently, whole-exome sequencing (WES) has been proven successful for the detection of clinically relevant point mutations and small insertion–deletions exome wide. We evaluate the utility of short-read WES (SOLiD 5500xl) to detect clinically relevant CNVs in DNA from 10 patients with intellectual disability and compare these results to data from two independent high-resolution microarrays. Eleven of the 12 clinically relevant CNVs were detected via read-depth analysis of WES data; a heterozygous single-exon deletion remained undetected by all algorithms evaluated. Although the detection power of WES for small CNVs currently does not match that of high-resolution microarray platforms, we show that the majority (88%) of rare coding CNVs containing three or more exons are successfully identified by WES. These results show that the CNV detection resolution of WES is comparable to that of medium-resolution genomic microarrays commonly used as clinical assays. The combined detection of point mutations, indels, and CNVs makes WES a very attractive first-tier diagnostic test for genetically heterogeneous disorders.

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